Classification of walnut varieties obtained from walnut leaf images by the recommended residual block based CNN model-Reference-Cited by-同舟云学术

Classification of walnut varieties obtained from walnut leaf images by the recommended residual block based CNN model

Published:2022-11-11 Issue:3 Volume:249 Page:727-738
ISSN:1438-2377
Container-title:European Food Research and Technology
language:en
Short-container-title:Eur Food Res Technol

Author:

Karadeniz Alper Talha^ORCID,Çelik Yüksel^ORCID,Başaran Erdal^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Biochemistry,General Chemistry,Food Science,Biotechnology

Link

https://link.springer.com/content/pdf/10.1007/s00217-022-04168-8.pdf

Reference34 articles.

1. Kulkarni K, Zhang Z, Chang L, Yang J, da Fonseca PCA, Barford D (2013) Building a pseudo-atomic model of the anaphase-promoting complex. Acta Crystallogr Sect D Biol Crystallogr 69(11):2236–2243

2. T. KARADENİZ, “Ordu Yöresinde yetiştirilen ceviz genotiplerinin (Juglans regia L.) seleksiyonu,” Ordu Üniversitesi Bilim ve Teknol. Derg., vol. 1, no. 1, pp. 65–74, 2011.

3. Khalesi S, Mahmoudi A, Hosainpour A, Alipour A (2012) Detection of walnut varieties using impact acoustics and artificial neural networks (ANNs). Mod Appl Sci 6(1):43

4. Esteki M et al (2017) Classification and authentication of Iranian walnuts according to their geographical origin based on gas chromatographic fatty acid fingerprint analysis using pattern recognition methods. Chemom Intell Lab Syst 171:251–258

5. L. U. Jun, X. Z. Han, and K. J. Wang, “Classification of Collection Walnut Based on GLCM and SVM,” in 2nd International Conference on Test, Measurement and Computational Method (TMCM 2017), 2017, pp. 276–281.

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Determination of concrete compressive strength from surface images with the integration of CNN and SVR methods;Measurement;2024-10

2. A novel approach for the non-destructive detection of shriveling degrees in walnuts using improved YOLOv5n based on X-ray images;Postharvest Biology and Technology;2024-08

3. Detection of Dangerous Human Behavior by Using Optical Flow and Hybrid Deep Learning;Electronics;2024-05-29

4. Diseases: CNN-SVM Integration;2024 2nd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA);2024-03-15

5. Walnut Leaf Disease Identification with Multi-Level CNN Architecture;2024 3rd International Conference for Innovation in Technology (INOCON);2024-03-01